machine learning framework 2

Creating Understandable Computational Models from Data

machine learning framework is a complete solution for business
and financial engineers, process and manufacturing engineers, quality
assurance professionals, and all experts who want to extract
computational models from data. Knowledge engineers and machine
learning experts, and others who search for a framework to develop
customized solutions, will also benefit from its future-looking fuzzy
variants of machine learning algorithms in an open architecture.

Reporter, the new higher-level user interface,
makes it possible to run a large number of
model-training tasks and then get an
overview and comparison of the performance of the different models that
were created.

With Reporter, you can test all permutations and combinations of different data
sets, algorithms and algorithm options. There are
various options for structuring and formatting the output.

Incremental saving makes it possible to continue with the calculations
after an interruption without having to complete tasks again.

To take advantage of the multicore revolution, it has parallelization built in, parallelizing model generation and cross model validation.

High-end architecture and machine learning approaches are very
similar: select the right methods and combine them intelligently in a
framework with mathematical and knowledge-based
technologies. machine learning framework has successfully
delivered this combined knowledge in a fast and robust solution for
industry leaders.

machine learning framework is developed and supported by
Software Competence Center Hagenberg (SCCH) GmbH, and is owned and
licensed by uni software plus GmbH.

About the Developers

Software Competence Center Hagenberg (SCCH) was founded in 1999 by
five institutes of the Johannes Kepler University Linz. As one of
Austria's largest independent research centers, SCCH is a harbinger for
software-related technological research and development trends.

uni software plus GmbH, a Mathematica reseller since 1990, is a
solution
provider in the field of computer mathematics, machine learning, and
data mining, serving quantitative finance and process industries.